Locating human resources via a computer network

ABSTRACT

A computer implemented method for searching and mapping includes: providing one or more databases that comprise a plurality of profiles representing a plurality of internet searchers; providing client devices that enable the plurality of internet searchers to enter search and map requests; creating a plurality of search spaces representing the plurality of internet searchers, each search space representing a respective internet searcher and comprising a respective search request record containing one or more previous search requests of the respective internet searcher, and each of the one or more previous search requests including one or more keywords entered by the respective internet searcher when performing a search; and receiving a search and map request including one or more keywords identifying one or more internet searchers that have previously entered the received one or more keywords in at least one previous search request from a current internet searcher.

CROSS-REFERENCE TO RELATED APPLICATIONS

This is a continuation application of U.S. patent application Ser. No.13/873,042, filed Apr. 29, 2013, which claims the benefit of U.S.Provisional Application No. 61/639,377, filed Apr. 27, 2012 and U.S.Provisional Application No. 61/732,089, filed Nov. 30, 2012, all ofwhich are herein incorporated by reference in their entirety.

COPYRIGHT NOTICE

A portion of the disclosure of this patent document contains materialthat is subject to copyright protection. The copyright owner has noobjection to the facsimile reproduction by anyone of the patent documentor the patent disclosure, as it appears in the Patent and TrademarkOffice patent files or records, but otherwise reserves all copyrightrights whatsoever.

FIELD OF THE DISCLOSURE

This disclosure relates to ways of locating human resources via acomputer network (e.g., the Internet) from keywords or phrasesassociated with the human resources.

BACKGROUND

There are many search engines on the internet that are used forsearching textual and pictorial information. Popular search enginesinclude, e.g., Google®, Yahoo! ®, Bing®, and the like. All popularsearch engines provide their results as lists of URLs (Uniform ResourceLocators) for the searched keywords.

There also exist virtual networks on the internet that link people.These fall into different categories:

Social Networks: Networks of friends or mutual acquaintances (such asFacebook® and Google+®)

Business Networks: Connect people based on their business relations andprofessional contacts (such as LinkedIn®)

Chat Rooms: These are rooms of predefined interests for discussions anddebates (such as PalTalk® and Yahoo!® chat rooms)

A traditional search engine's main service is normally just to providethe searcher with a list of URLs where the keyword appears on thirdparty websites.

A number of problems exist from a searcher's perspective. For example,although sometimes a searcher/user can get a solution to a question theyare researching using their own searches of documented information onthe Internet, they might obtain more knowledge or get a better resultfrom “unwritten” experience or advice from a person (i.e., a “humanresource”) who has knowledge or experience in relation to the questionthey are researching.

SUMMARY

In general terms, this system facilitates locating human resources(i.e., people or groups of people) over a network, such as the internet,based on one or more specific keywords entered by a user. Someembodiments additionally facilitate connections between the user and thehuman resources they locate, for example so they can chat online orexchange messages and resources to discuss a particular area ofinterest. In the following, the term, “human resources,” refers to anindividual person or group of people. Typically, these people will beusers of the network. Additionally, for simplicity, the term,“keywords,” will be used to refer to “keywords” and “phrases.”

Embodiments of the system comprise a database of human resources, asearch engine for querying the database and, optionally, a chattingcomponent. The database contains interests of individuals or groups ofindividuals (i.e., human resources), as expressed by them in terms ofkeywords. The database preferably also includes contact details (e.g.,email addresses, social network IDs, and the like) for each humanresource to facilitate contact between a user querying the database andthe human resources returned by their search. The search engine receivesa query and searches the database for possible matches before storingthe query itself in the database with the corresponding contact addressof its creator. Once the query finds one or more matching humanresources, a list of those resources is returned to the user along withthe matched keywords, who may then be offered a chance to communicatewith the human resource(s) found by the search, for example via thechatting component where present. This gives rise to a new kind ofsearch engine that produces what may be called HRLs (Human ResourceLocators) as opposed to the standard URLs produces by current searchengines.

In one variant of the system, all search queries entered in traditionalinternet search engines are considered keywords/phrases expressinginterests of their originators. Thus, the system stores them in adatabase along with the contact addresses of their originators forpossible networking in future runs. As soon as the query is entered, theuser is notified of previous users who have entered similar queries andis thus given the opportunity of communicating with them.

In some embodiments, the system creates a network of internetsearchers/users via a “Search and Map” mechanism, where the Internetuser searches for a specific keyword/phrase using popular search engines(e.g., Google®, Yahoo! ®, Bing®) and later can connect to other userswho have searched (or are currently searching) for a similarkeyword/phrase. This helps users know each other and share informationbased on performed searches.

One aspect of the system provides a computer-implemented method for auser of a network (e.g., the Internet) to locate one or more humanresources, the method comprising the steps of:

providing a record in a database for each of a plurality of humanresources, the record including one or more keywords associated with thehuman resource;

receiving from a first user a search request including one or morekeywords;

searching the records in the database to find matching recordsassociated with one or more human resources with a keyword that matchesa keyword in the received search request; and

returning search results to the first user, the search resultsidentifying the matching records.

Each human resource record may additionally comprise contact informationfor the human resource. In this case, the search results returned to thefirst user may provide the first user with an opportunity to contact theone or more human resources using the contact information from thedatabase records for those human resources.

The search results returned may be, in effect, a list of HRLs (HumanResource Locators).

The keywords entered by the first user to initiate the request arepreferably added to the database record for the first user (who maythemselves be a human resource with a record in the database). In thisway the keywords associated with users in their associated humanresource database records can evolve over time based on the searchesthat each user is conducting. Users are preferably also given theability to amend the keywords in their human resource database record,preferably including the ability to delete and/or amend existingkeywords and/or to add new keywords.

In some embodiments, the step of receiving the keywords from the firstuser comprises receiving keywords that the first user has entered into asearch engine for the purposes of a conventional internet search.

In some embodiments a link can be created in the database betweenmatching records to create a virtual network of human resourcesassociated with particular matching keywords. Where such links areformed the human resources associated with the linked records arepreferably notified.

In another aspect the system provides an improved Internet search enginewhich makes use of a database that distinguishes between human resourcesand material resources (e.g., documents and other files accessible viathe internet). Embodiments of this aspect may make use of at least onefirst database for maintaining records for human resources and at leastone second, separate database for indexing material resources.Alternatively, records for human resources and material resources may bemaintained in the same database, wherein the database includes a flagthat distinguishes human resources from material resources. A user mayselect to have search results returned to them that identify only humanresources (e.g., a list of HRLs), only material resources (e.g., a listof URLs) or a mixture of the two.

A further aspect of the disclosed embodiments provides a systememploying a method as described in the first aspect. This may take theform of a program embedded in an internet browser (e.g., a tool bar), ora dedicated web page, for example.

BRIEF DESCRIPTION OF THE DRAWINGS

An example is now described with reference to the accompanying drawings,in which:

FIG. 1 shows a schematic of modules for an embodiment;

FIGS. 2(a) to (c) show exemplary user interface layouts for steps in aprocess of using a system in accordance with an embodiment;

FIG. 3 shows a process flow diagram for a process of using a system inaccordance with an embodiment; and

FIG. 4 shows a schematic of a network architecture in which the systemof an embodiment can be implemented.

DETAILED DESCRIPTION

The internet is primarily used to connect users to resources. Theseresources usually take the form of web materials such as documents,videos, sound tracks, software, and the like (i.e., material resources).However, these resources can also take the form of humans who possessspecific knowledge or interests. In the former case, the user intends toaccess the located resource, whereas in the latter case the user intendsto communicate with it. Communicating with “previously-known” humanresources (acquaintances) is a well-established service in the internet.The prevailing channel for such communication is emailing which isreported to be the number one internet activity according to recentstatistics. Other ways of contacting acquaintances include socialnetworking services such as Facebook and Google plus. Nonetheless,sometimes internet users may desire to contact humans who happen to bepreviously unknown to them based on interest, knowledge, expertise oreven need for a one-time tip. In this situation, locating such humansthrough the internet is not an easy task. If the user is already amember or a forum or a discussion group then she may try to find thetargeted resource from within that forum or group. However, thissolution is not always useful especially if the user would like tocontact people of different interests or on matters that are notdirectly related to the subject of interest of the concerned group orforum. Moreover, the search space in such a case will be limited to thesubset of potential resources bounded by the members of the specificgroup/forum.

Perhaps the most comprehensive and straightforward approach for tacklingthis problem is using a search engine. To communicate with people whohave specific interests, a searcher would usually think of a keyword (ora series of keywords) that characterizes this interest in some form inhopes that this search would generate a list of URLs containing leads tohuman resources who would be willing to communicate with him. Theseleads can be in forms of blogs, personal webpages, forums (to whichmembers are affiliated), published resumes, Facebook pages, discussiongroup, and the like. However, there is no form of querying that cansolely lead to URLs of this kind only. Typically, the resultant URL listdoes not differentiate between human resources and material resources;therefore, a mixture of both is passed on to the searcher. Any attemptof adding keywords that tell the search engine to filter human resourcesnot only will result in an elimination of the undesired materialresources, but will instead only limit the search scope. This is due tothe fact that search engines locate internet resources by conducting afull text search on the documented script pertaining to those resources.Even if a search result provides a lead to a human resource such as arésumé of a person, there is no guarantee that the keywords used in thesearch is of a particular interest to that person; since it can be apart of a description (e.g., address) of a business entity with which heor she had a contact during their career path or for which an oldmanager of theirs is currently working.

It may seem that the closest available channel to locate previouslyunknown human resources is to use social networking services, instantmessaging services or chat rooms. However, all means of expandingfriends/acquaintances/interests in these services are predefined. Friendfinders are programmed by their manufacturers where the user has nooption but to select from what they provide her with. Chat rooms areequally limited by providing access to only a limited segment of userswith predefined interests. Even the available criteria for searchingwithin these existing users are predefined; where the manufacturer ofthe site (such as Facebook®, for example) limits the filtration processby factors like age, gender and location. Since you cannot search bypersonalized terms (such as preferred meals, which may be nocturnal orvegetarian) or any other arbitrary sequence of keywords, this limits thesearch space and confines it to a sub-group of members or a sub-group ofchoices. Even if privacy breaching issues are resolved, and a user isindeed allowed to search the full space of other members, more confusionwill arise in the search results. This is due to the mechanism of thefull text search pointed out earlier. The user will always get hits thatwere only considered because a series of keywords happened to exist inthe “wall” space of some members for any number of reasons. It is veryplausible that none of these members have consciously included orallowed such a series of keywords to be on their wall; and even if theydid, it is very unlikely that they would have done so for the purpose ofbeing “found” by other members through such a searching process.

Google plus introduced “Discussions” in their search engines in October2009. The purpose (as stated by Johanna Wright, Director of ProductManagement and Devin Mullins, Software Engineer, Google) was to “findforum posts or discussions related to what you're searching for.” Theyfurther elaborate by saying that it is always nice to know what othersare saying about a specific topic and how recent their comments are. Yetagain, this service is not intended to connect you to people for thepurpose of making discussion/chatting about the subject of yourinterest; rather, it deals with previous comments of people filtered bydiscussion groups and forums and uses the search engine to locate them.So once more the service targets mini documents consisting of shortparagraphs commenting on a subject or an incident instead of targetingthe person creating these “comments.”

The problem of locating human resources on the internet is unique. Itinherits its difficulty from the fact that humans are arguablyfree-willed entities that make varied decisions during their lifetime.Any other internet resource can be primarily classified in a categorythat defines its scope and puts it in its place within the globalframework of human interests. The same, however, cannot be said forhumans for two main reasons. The first is due to the vast number ofchoices and decisions humans make every day. Each decision or choicecarries an experience that may, in principle, be of interest to otherhumans. Thus, it is very difficult, if not practically impossible, tocategorize human beings in the same way one categorizes software, books,movies and other martial internet sources. The second reason is due tothe fact that humans almost continually change their behavior, interestsor aspirations. A ten year old boy may have a growing interest incomputer games and skate boarding. The same boy five years later wouldprobably have entirely different interests. On the contrary, the HarryPotter fiction series, for example (categorized under fiction—fantasysub-category), is very unlikely to be categorized under a differentgenre within the next decade. This difference between the nature of“human” versus “material” resources warrants a new way of tackling theproblem of accessing human resources over the internet. In summary, thisnew way has to make use of and account for the following seven points:

1. The fact that unlike material resources accessible by internet searchengines, humans are free-willed entities who make an uncountable numberof choices and decisions on a daily basis that may potentially be ofinterest to other humans; therefore, making it practically impossible toclassify them using a set of categories the same way material resourcesare categorized.

2. The fact that unlike material resources accessible by internet searchengines, humans are adaptive, aging creatures who change their interestsand aspirations over time.

3. The fact that unlike material resources accessible by internet searchengines, humans are living creatures who are prone to illness and deaththus becoming “inaccessible” to other human beings.

4. The fact that unlike material resources accessible by internet searchengines, humans may opt not to be contacted by others depending on whothey are contacted by, the subject of contact, the time of contact orany other conceivable reason.

5. The fact that unlike material resources accessible by internet searchengines, humans can express their interests in terms of a set ofkeywords.

6. The fact that unlike material resources accessible by internet searchengines, humans can edit the set of keywords described in point 5 byadding more keywords to it or removing all or some of the keywordscontained in it or editing them.

7. The fact that humans are and have already been expressing theirinterests in the same way described in point 5 when attempting to accessmaterial resources over the internet using variant search engines.

Generally, embodiments of the system address the problem of locatingpeople over the internet as opposed to documented material (documents,videos, sound tracks, and the like) traditionally queried by currentsearch engines. From the networking point of view, embodiments of thesystem themselves create and destroy links (e.g., communicationchannels) between users based on their list of interests (keywords);unlike what happens in traditional networking services, where the useris responsible for creating and destroying these links.

In classical user networks, it is the responsibility of the user to addor delete other users. In a user network in accordance with someembodiments this is done automatically as a user performs more searches(potentially adding more users if the searched topic is not novel—whichis the usual case) or deletes certain keywords from his profile. Thismeans that less “maintenance” is required by the user, who pays noattention to the dynamicity of the underlying network topology. If theuser wants to keep permanent ties to other users, the user can revert tostandard methods of communication, e.g., email.

It should be noted that this system is different from social networks,instant messaging services or chat rooms—all these share the property of“user-driven links,” which means that the user always select who theuser links to himself Besides, all “expansion rules”—means of expandingthe user's friends/acquaintances/interests—are predefined: “Friendfinders” are programmed by their manufacturers, and the user has nooption but to select from what they are provided with. Chat rooms aresetup with predefined interests. Even the available criteria forsearching existing users are predefined—once a manufacturer (such asFacebook®, for example) provides searching by age, gender and location,you can't search by exotic terms like preferred meals, is nocturnal oris vegetarian. Even if this set of provided search criteria grows, youare still searching what the user writes in his profile, not everythingthat the user has written on Facebook®—which is a different scope. Ineffect, some embodiments convert every search query to an “expansionrule,” i.e. every search query becomes a means of locating a new user.

Some embodiments of the system address the problem of locating humanresources over the internet by building a database consisting ofkeywords entered, edited and managed by individuals who would be willingto be contacted by others based on these keywords. Each user (i.e.,human resource) would have her own editable user space that contains herprofile information, contact address and the specific list of keywordsby which she chooses to define herself and her interests. The systemmaps/matches all users (i.e., human resources) together based on theirinterests (the keywords existing in their space). Subsequently, theusers would be offered the option to connect to others upon highlightinga keyword in their list or when entering a new keyword. The networkstructure (connecting users to each other) would typically bedynamically changing as users change their list of interests byremoving, adding or editing a keyword in it. Whenever a user enters anew keyword, the search engine queries the database and provides herwith a contact list containing direct access to other users who areinterested in the same keywords. The resultant contact list is parallelto the URL list provided by traditional search engines when queried formaterial resources. In this regard, it can be termed an HRL (humanresource locator) list.

As a concrete example of how the system may be useful, consider thatAlan, a British undergraduate student, wants to transfer to StanfordUniversity. An elegant way would be to search for (transfer StanfordUniversity international students) and filter the results in such a waythat he is left with students who have gone through a similar experiencewithin the last year. This will enable him to communicate directly withthose students who have transferred or applied for a transfer to theuniversity within the past year to ask them for tips and advice formaximizing his chance of getting an approval. Note that he would only beconnected to those users who have opted to keep the relevant keywords intheir “search space” (i.e., their database record) and thus are willingto be communicated to regarding this subject.

Some embodiments can provide users with a management tool for editingand changing their preferences, and by monitoring the heartbeat of theiractivity over time. If the user stops using the service or interactingwith it for some time, then she would be deemed unreachable and hencetaken out from the network.

One way of implementing the system is to make use of current searchengines. Queries passed to search engines may be considered as keywordsrepresenting interests of users. Thus the system can make use of thisalready existing activity to build its database, then allow users torevise and edit their lists of keywords as deemed fit.

The system can be used by any existing service such as social networkservices, forums or discussion groups. It can also be used bytelecommunication or mobile companies that connect their users togetherthe same way, for instance, as the Blackberry Messenger Service.

Furthermore, some embodiments archive interests for the purpose ofseeding future networks. While traditional search services have aseparate process for archiving documents (and other resources) for thepurpose of querying, this system will have a recursive loop, feeding thequery itself to the targeted database for the purpose of future queries.Imagine a person (x) wanting to start an association of Europeanzoologists who served in Kenya during the past decade, and noinformation is available regarding that issue; whenever somebody else(y) thinks about the same idea, both x and y will be informed of eachother and a network pertaining to the above keywords is established.This gives rise to a network seeding utility, where anybody searchingfor a new combination of keywords is essentially seeding a new networkbetween those interested in the same thing.

Yet another characteristic of this system is realized as more usersstart making use of it. Current search engines play the role of agateway between users and online documented information (e.g., webpages, pictures, videos, and the like). Similarly, a user network willpresent a gateway between users and “potential experts.” The assumptionis that as an individual searches the internet using, for example, akeyword like “quantum entanglement,” the user gains some level ofexpertise on the subject. This level may be preliminarily assessed, forexample, by the number of “sessions” the user has been searching usingthe same (or similar) keywords. A further refined level of assessmentcan be applied using feedback from other users once this “expert” isapproached by them. So the system may finally present a new gateway,parallel to that offered by search engines, but differing from it inthat it provides the user with a network of expertise knowledge residingin human minds. In a sense, this will complement the role of currentsearch engines in giving accessibility to undocumented human knowledgeand experiences, and will also provide a means that encourages people tomaintain, expand and exchange their experiences in every expressiblesubject. Furthermore, since the knowledge pursued by this system is inthe human mind, and since humans change their interests over time, theonly way to maintain this knowledge is to transfer as much as possibleof it to other human minds before its holder changes his interest orceases to exist. This system provides a means for such a process where“blogs” and “pages” propagate animatedly in the human mind space of theinternet users.

While it is conceivable that an internet user could use a search engineor a social network service (or any other tool such as Discussions byGoogle) to locate human resources over the Internet, this process wouldbe very different than the system and method disclosed herein. Forexample, an architecture student who needs a private one to one tutoringon AutoCAD© or Rivet© (special software programs for architecturaldesign) may use a search engine like Google to locate such a resource.Let's assume that the probability of having a search engine user whotargets a human resource is k. In such a case, the location processusually encompasses several layers before accomplishing its mission.Since the engine does a full text search in targeted web pages,comments, posts, blogs, and the like, it can always produce twoundesired outputs:

-   -   Results which pertain to material resources rather than human        ones.    -   Results which pertain to human resources but are irrelevant to        the entered query (see above).

No matter how the search process is optimized to avoid such irrelevantresults, there will always be a probability of showing them, as the fulltext search property inherently produces such results. Let's denote thisprobability by p. Subsequently, if each search query on average producesan amount of internet traffic equal to f, then for each search query,again on average, there will be irrelevant internet traffic (IT) equalsto:

IT=p×k×f  (1.1)

From (1.1) the on average relevant internet traffic per search query(RT) is:

RT=(1−p)×k×f  (1.2)

Although the RT provides URLs relevant to human resources, there willalways be a probability w of having URL's amongst them that do notprovide direct communication channels to those humans. To actuallycontact those humans, other steps are needed such as accessing a forumwebpage and registering in such a forum before being able to communicatewith its members. This extra step will cost extra g traffic on averageper URL. The on average extra irrelevant traffic (EIT) for this scenariowill then be given by:

EIT=(1p)×k×w×g  (1.3)

Moreover, unlike non-human resources, people may be unwilling to becontacted; and thus, the whole search effort leads to a dead end. Assumethat the probability of that happening is q; then the on-average wastedtraffic (WT) in this regard will be:

WT=q×(1−p)×k×f+q×(1−p)×k×w×g

or

WT=q×k×(1−p)×(f+w×g)  (1.4)

Adding up all on average irrelevant and wasted internet traffic inequations 1.1, 1.3 and 1.4, the total irrelevant/wasted traffic (IWT)will be given by:

IWT−k×p×f+(1−p)×k×w×g+q×k×(1−p)×(f+w×g)

or

IWT=k×p×f+(1−p)×k×(w×g+q×(f+w×g))

or in a more compact form:

IWT=k×{p×f|(1p)((w×g|q×(f|w×g))}  (1.5)

Based on the above, it is argued that the system will save internettraffic equivalent to IWT given by equation 1.5. The traffic generatedby embodiments of the system itself will be much less than the trafficsaved since it would be directed towards the objective of the search(i.e., the human resources); where human resources are represented bycontacts only, which is far less in terms of traffic than traditionalmaterial resources.

Furthermore, if adopted by current search engines, this system wouldincrease their efficiency by making them avoid producing suchunnecessary traffic; caused by users searching for human resources. Suchusers would then have a proper channel to address their search querieswith less cost of search and network throughput. This will makesearching for traditional material resources more efficient since theengine would now have less queries and less amount of traffic tocommunicate (as indicated by equation 1.5). In other words, the systemwill improve current search engines by decomposing them into twocomponents; one which provides for searching material resources, asnormal, while the other provides for searching human resources. Thelatter would be designed in a way that capitalizes on the nature andcharacteristics of the resources it is supposed to search (as explainedabove).

It is also important to note that this taxonomy of human versus materialinternet resources is unique. It cannot be compared to any othercategorizations, like document versus software or sound tracks versusvideo clips. This is due to the specific characteristics of humanresources summarized above; which cannot be attributed to any of thesub-categories of material resources. Therefore, disclosed embodimentsachieve far more than merely addressing a problem by arbitrarilydividing it into smaller parts and solving each part alone. Thedisclosed embodiments tackle a poorly addressed problem by attending toa unique subcategory of internet services; consequently improving itscounterpart and thereby increasing the overall efficiency of internetsearch engines in general.

Embodiments of the disclosed system and method have one or more of thefollowing advantages:

-   -   Find other users looking for or interested in similar subjects        (based on keywords).    -   Instant communication between users based on keywords.    -   Creates “networks of searchers/users” on the fly.    -   The network structure evolves seamlessly and naturally, with        minimal user intervention.    -   Enables the existence of specific networks of users that would        otherwise be very hard to create, such as a community of mothers        sharing the experience of certain children syndrome in a        particular region.    -   Creates a way of archiving interests, potentially linking        prospective users who might develop the same interest in the        future (even if no links currently exist).

In some embodiments, links between users are based purely on keywords,which makes the network topology adaptive and continually reflective ofthis intention.

In some embodiments, users can manage their own search space (i.e.,database record comprising searched keywords) by removing unwantedkeywords.

In some embodiments, communication between searchers is allowed only ifthe common keyword still exists in both search spaces.

In some embodiments, users can filter their fellow searchers/users bytime frame, location, online/offline status and other features. Forexample, when a user selects a time frame of interest, the user cancommunicate with other searchers/users who used the same keywords withinthat specific time frame. In other words, if the “Last 24 Hours” timeframe is used, then the user would be provided with the list of onlythose searchers who have searched for (or entered) the same keywordswithin that specific time frame.

In some embodiments, users can sort their fellow searchers/users byrelevance of keywords, time frame, geographical location and otherfeatures.

In some embodiments, upon communication, users can like/rate others;e.g., based on the usefulness of their experience in communicating withthem with respect to the used keywords.

In some embodiments, users can enable a feature of an embodiment toprofile their search (interest) history (referred to in the example as“Profile Me”). This facilitates calculating similarity measures betweensearchers, which can be used to provide the user with top matchesamongst all other users.

In some embodiments, once the database is built, finer levels ofinformation can be incorporated. For example if a user enters a keywordlike “US Stock Market,” he is allowed to use further reserved “operands”for indicating his level of expertise/interest in the entered keyword.Based on that, he can opt to contact or be contacted only with aspecific category of users. Examples of such reserved operands are:

-   -   US Stock Market {?}: The user is novice and looking for        information.    -   US Stock Market {i}: The user has (unprofessional/amateur)        information.    -   US Stock Market {p}: The user has professional knowledge.    -   US Stock Market {a}: The user has academic knowledge.    -   US Stock Market {b}: The user is a business entity.    -   US Stock Market {n}: The user is a not-for-profit entity.

Continuing to look at an exemplary embodiment, the system can belogically divided into five main modules. Refer to FIG. 1 for apictorial depiction:

I. Input Control

This component is a webpage or a mobile application for the user toenter the desired keywords. If the system is used in conjunction with acurrent search engine, a Widget/Gadget/ActiveX or even a toolbar that isinstalled on top of the browser could be used. Let's call this component“the control” from here-on-after.

Here, the keywords are saved to the user's profile (along with atimestamp). When the user clicks Locate Searchers in the component, oursystem looks for similar previously-entered searches and displays theresults accordingly.

In case of using the control in conjunction with a search engine, thekeywords are grabbed to be processed as above, then released to pursuethe normal search process.

II. Output Control

The results include the list of people who have used similar keywords inthe specified time frame, location, and the like. (“HRLs”), along with amap of their general location for better visualization, when the userhovers over these points, he can view the details of other users.

III. Chatting Utility

Once a user locates another user, they can communicate using ourchatting application, possibly extending that acquaintance outside thesystem to standard networks, such as Facebook, Twitter, and the like.

IV. Underlying Database

To implement this scenario, a database is maintained with the followingfields:

-   -   Username (can be her OpenID (Gmail, Yahoo!, Hotmail . . . ) or a        new one provided by our service)    -   Password    -   City    -   Province    -   Country    -   Used Keywords    -   Status (Offline/Online/Busy/Away . . . )    -   Get Connected (If checked, other searchers can communicate with        the user, if not, communication can only be initiated by the        user)    -   Ignore Session (Keeps the user connected to others who have        searched for the same keywords entered during this session,        without adding the keywords to the user's space)    -   Profile Me (Enables/Disables the Profile Me option described        above)

V. User Space

The service creates a “Search Space” for the searcher/user to managetheir keywords. This allows the searcher/user to:

-   -   delete keywords    -   archive keywords    -   export/import keywords to other formats    -   export searchers list to, e.g., Microsoft Excel®, Microsoft        Outlook®, and the like.    -   Block, e.g., specific searchers, block by country, block by IP,        and the like.

The “Search Space” also forms part of the user profile and is stored ina database.

Embodiments may be implemented in a number of ways, including, forexample, one or more of:

-   -   A dedicated website    -   Integration into existing browsers (for example, integrated into        the toolbar of an existing Internet Browser)    -   Integration into censorship gateways    -   Integration into a specific search engine    -   Integration into a specific existing social network service    -   Integration into a specific mobile/telecommunication service

The following, also shown schematically in FIG. 3, is an example flow ofsteps to make use of a disclosed embodiment:

1. Access the control webpage (or install it, then access it, in case ofusing the invention in conjunction with existing service; for example,install the control in an Internet Browser). FIG. 2(a) shows anexemplary user interface screen layout for login to/registration withthe control webpage.

2. Register for the service by entering the Username, Password, Country,City, Province, Get Connected, Profile Me and other relevant information(see FIG. 2(a)).

3. Enter keywords in the control webpage (see FIG. 2(b)).

4. Click “Locate”—the application will then display the list of users(i.e. a list of “human resources” or “HRLs”) with similar interests in atabular format together with a map showing where the users are located(see FIG. 2(c)). When the user hovers over these points, relevantinformation will be displayed.

5. Send instant messages (IMs) using the chatting application to talkand share information about the subject at hand (see FIG. 2(b)), orshare contact details to communicate elsewhere (e.g. Facebook®,Twitter®, and the like).

Other features incorporated in some embodiments include:

1. When users chat based on a keyword and exchange Internet resources(URLs), those resources will be stored in the application and tagged bythe keyword for later usage.

2. In case any of the users of similar interest is offline, a user cansend her an offline message, which she can view once back online again.

3. A user will also be shown a list of trending keywords that otherusers are actively searching. When clicking on one of them, a list ofrelated users, as described in 4, will be shown.

4. When a first user searches for a novel keyword, where no other usershave similar interest related to it, her search query will be saved; andwhen some other user(s) search for the same keyword later on, the firstuser will be notified.

5. A user can ask to create a public online event (e.g., a videolecture) related to some keyword through the application, where otherusers can ask to join this event.

6. When used with search engines (with the user's approval), the systemcan track URLs visited based on searched keywords. This can be sharedwith other users as a “suggested solutions” list of URLs.

FIG. 4 shows a network architecture in which an embodiment can beimplemented. In this example, database 42 stores records for users(“human resources”). Each user record includes keywords that representtopics and fields of interest to the user, along with contact detailsfor the user. The contact details may include one or more of a username, an email address, an instant message or social network ID, atelephone number or other contact information. Each record preferablyalso includes a geographical location for the user.

The database 42 is accessed by a search engine application executing ona search server 40. In this example, the server 40 has direct access tothe database 42. In other examples the server 40 may access the database42 via the Internet 50 or other communications network. Users connect tothe search server using Internet connected client devices 44, 46.

In this example, a first user accesses the search server from a firstclient device 44. They query the database 42 in the manner discussedabove using one or more keywords. The search results identify twofurther users who are currently online, using client devices 46, andpresents the first user with a list containing the HRLs for these twofurther users to give the opportunity for the first user to communicatewith these other users via the Internet 50. The communication may beeffected, for example, via a chat application executing on the sameserver 40 as the search engine application. Alternatively, communicationmay be affected by another server 48, which may for example be a thirdparty chat server.

It can be seen from the above that disclosed embodiments make use of theunique taxonomy of human vs. material resources, offering an approachand system that addresses the problem of locating human resources overthe Internet in a much more efficient manner than is possible withconventional search engines; for example, offering significant internettraffic and bandwidth savings as demonstrated above.

The skilled person will appreciate that various modifications to thespecifically-described embodiment are possible without departing fromthe spirit and scope of the disclosed embodiments.

What is claimed:
 1. A computer implemented method implemented over anetwork for searching and mapping, the method comprising: providing acommunications network that enables communication between one or moredatabases and one or more search servers, wherein the one or moredatabases comprise a plurality of profiles representing a plurality ofinternet searchers, the one or more databases accessed by search engineapplications executed by processors on the one or more search servers;providing client devices connected to the one or more search servers viathe communications network, wherein the client devices enable theplurality of internet searchers to enter search and map requests and tosend entered search and map requests to the one or more search serverswhen using the internet search service; creating a plurality of searchspaces representing the plurality of internet searchers, wherein eachsearch space representing a respective internet searcher of theplurality of internet searchers and comprising a respective searchrequest record containing one or more previous search requests of therespective internet searcher, wherein each of the one or more previoussearch requests includes one or more keywords entered by the respectiveinternet searcher when performing a search using the internet searchservice; receiving a search and map request including one or morekeywords identifying one or more internet searchers of the plurality ofinternet searchers that have previously entered the received one or morekeywords in at least one previous search request from a current internetsearcher; maintaining the received one or more keywords in a searchrequest record of a search space of the current internet searcher, andstoring the search space of the current internet searcher in the one ormore databases; searching the plurality of search spaces in the one ormore databases and identifying one or more search request records of theone or more internet searchers by matching the received one or morekeywords with at least one keyword in the plurality of search spaces;creating a search and map virtual network by generating one or morelinks from the identified one or more search request records of the oneor more internet searchers and search request record of the currentinternet searcher; storing the created search and map virtual network ineach search space of the one or more internet searchers and currentinternet searcher in the one or more databases; identifying the one ormore internet searchers from the identified one or more search requestrecords; returning a search result comprising a list of the identifiedone or more internet searchers; and displaying the search result alongwith a world map of the respective location of the identified one ormore internet searchers to the current internet searcher.
 2. The methodof claim 1, further comprising: creating one or more lists of interestsbased at least in part on one or more keywords of previous searchrequest records entered by the one or more internet searchers of thecreated search and map virtual network.
 3. The method of claim 2,further comprising: storing the one or more list of interests in atleast one search space of one or more internet searcher of the createdsearch and map virtual network.
 4. The method of claim 3, furthercomprising: editing the one or more keywords in the one or more lists ofinterests by the one more internet searchers in their respective searchspace.
 5. The method of claim 4, further comprising: automaticallyupdating the one or more links of the created search and map virtualnetwork based on the editing of the one or more keywords in the lists ofinterests.
 6. The method of claim 5, further comprising: dynamicallychanging a structure of the created search and map virtual network tocreate a changed search and map virtual network, and updating at leastone search space of one or more internet searchers of the created searchand map virtual network, in response to the updating of the one or morelinks.
 7. The method of claim 6, further comprising: notifying one ormore internet searchers of the changed search and map virtual network ofthe structure change.
 8. The method of claim 1, wherein each of theplurality of profiles representing a plurality of internet searchersincludes contact information, and wherein the search result returned tothe current internet search provides the current internet search with anopportunity to contact the plurality of internet searchers using thecontact information.
 9. The method of claim 1, wherein the one or morelinks are removed in the one or more databases if the associatedparticular matching keywords are removed.
 10. The method of claim 1,further comprising: selecting one or more filters that are applied tothe search result.
 11. The method of claim 9, wherein at least one ofthe filters is selected from: geographical location of the internetsearchers, time frame within which an internet searcher's matchingkeyword was created, online/offline status of the plurality of internetsearchers.
 12. A networked computer system implemented over a network,the networked computer system comprising: one or more search servers,each of the one or more search servers having a processor; acommunications network that enables communication between one or moredatabases and the one or more search servers, wherein the one or moredatabases comprise a plurality of profiles representing a plurality ofinternet searchers, the one or more databases accessed by search engineapplications executed by processors on the one or more search servers;client devices connected to the one or more search servers via thecommunications network, wherein the client devices enable the pluralityof internet searchers to enter search and map requests and to sendentered search and map requests to the one or more search servers whenusing an internet search service; each of the one or more search serverscomprising a processor configured to: create a plurality of searchspaces representing the plurality of internet searchers, wherein eachsearch space representing a respective internet searcher of theplurality of internet searchers and comprising a respective searchrequest record contains one or more previous search requests of therespective internet searcher, wherein each of the one or more previoussearch requests including one or more keywords entered by the respectiveinternet searcher when performing a search using the internet searchservice; receive a search and map request including one or more keywordsidentifying one or more internet searchers of the plurality of internetsearchers that have previously entered the received one or more keywordsin at least one previous search request from a current internetsearcher; maintain the received one or more keywords in a search requestrecord of a search space of the current internet searcher, and store thesearch space of the current internet searcher in the one or moredatabases; search the plurality of search spaces in the one or moredatabases and identify one or more search request records of the one ormore internet searchers by matching the received one or more keywordswith at least one keyword in the plurality of search spaces; create asearch and map virtual network by generating one or more links from theidentified one or more search request records of the one or moreinternet searchers and search request record of the current internetsearcher; store the created search and map virtual network in eachsearch space of the one or more internet searchers and current internetsearcher in the one or more databases; identify the one or more internetsearchers from the identified one or more search request records; returnsearch result comprising a list of the identified one or more internetsearchers; and display the search result along a with a world map ofrespective location of the identified one or more internet searchers tothe current internet searcher.
 13. The networked computer system ofclaim 12, wherein each of the one or more search servers comprises aprocessor configured to: create one or more lists of interests based atleast in part on one or more keywords of previous search request recordsof entered by the internet searchers of the created search and mapvirtual network.
 14. The networked computer system of claim 13, whereineach of the one or more search servers comprises a processor configuredto: store the one or more list of interests in at least one search spaceof the one or more internet searchers of the created search and mapvirtual network.
 15. The networked computer system of claim 14, whereineach of the one or more search servers comprises a processor configuredto: edit the one or more keywords in the one or more lists of interestsby the one more internet searchers in their respective search space. 16.The networked computer system of claim 15, wherein each of the one ormore search servers comprises a processor configured to: automaticallyupdate the one or more links of the created search and map virtualnetwork based on the editing of the one or more lists of interests. 17.The networked computer system of claim 16, wherein each of the one ormore search servers comprises a processor configured to: dynamicallychange a structure of the created search and map virtual network tocreate a changed search and map virtual network, and update the at leastone search space of one or more internet searchers of the created searchand map virtual network, in response to the update of the one or morelinks.
 18. The networked computer system of claim 17, wherein each ofthe one or more search servers comprises a processor configured to:notify one or more internet searchers of the changed search and mapvirtual network of the structured change.
 19. The networked computersystem of claim 12, wherein the client devices are selected from a groupconsisting of internet connected personal computers, personal digitalassistants, set top boxes, games consoles, or smart phones.
 20. Thenetworked computer system of claim 12, further comprising: an inputcontrol module displayed on each client device, via which a user canenter keywords for a search; and an output control module displayed oneach client device, via which a user can view search result from asearch to identify internet searchers with associated keywords thatmatch keywords they have entered via the input control module.
 21. Thenetworked computer system of claim 20, wherein the input control moduleis a webpage.
 22. The networked computer system of claim 20, furthercomprising including a search space in a user space module within whichan internet searcher manages respective database records, includingmanaging one or more keywords of one or more previous search requests.